Angiotensin II up-regulates sodium-glucose co-transporter 2 expression and SGLT2 inhibitor attenuates Ang II-induced hypertensive renal injury in mice
Bibliographic record
Abstract
Clinical trials indicate that sodium/glucose co-transporter 2 (SGLT2) inhibitors (SGLT2i) improve kidney function, yet, the molecular regulation of SGLT2 expression is incompletely understood. Here, we investigated the role of the intrarenal renin-angiotensin system (RAS) on SGLT2 expression. In adult non-diabetic participants in the Nephrotic Syndrome Study Network (NEPTUNE, n=163), multivariable linear regression analysis showed SGLT2 mRNA was significantly associated with angiotensinogen (AGT), renin, and angiotensin-converting enzyme (ACE) mRNA levels (P<0.001). In vitro, angiotensin II (Ang II) dose-dependently stimulated SGLT2 expression in HK-2, human immortalized renal proximal tubular cells (RPTCs); losartan and antioxidants inhibited it. Sglt2 expression was increased in transgenic (Tg) mice specifically overexpressing Agt in their RPTCs, as well as in WT mice with a single subcutaneous injection of Ang II (1.44 mg/kg). Moreover, Ang II (1000 ng/kg/min) infusion via osmotic mini-pump in WT mice for 4 weeks increased systolic blood pressure (SBP), glomerulosclerosis, tubulointerstitial fibrosis, and albuminuria; canaglifozin (Cana, 15 mg/kg/day) reversed these changes, with the exception of SBP. Fractional glucose excretion (FeGlu) was higher in Ang II+Cana than WT+Cana, whereas Sglt2 expression was similar. Our data demonstrate a link between intrarenal RAS and SGLT2 expression and that SGLT2i ameliorates Ang II-induced renal injury independent of SBP.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".